Far-side Active Regions Based on Helioseismic and EUV Measurements: A New Data Set for Heliospheric Machine Learning Advancements
Active Regions (ARs) are regions of strong magnetic flux in the solar atmosphere. Understanding the global evolution of ARs is critical for solar magnetism as well as for accurate space-weather forecasting. We present the first far-side AR data set based on EUV observation and helioseismic measureme...
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IOP Publishing
2024-01-01
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| Series: | The Astrophysical Journal |
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| Online Access: | https://doi.org/10.3847/1538-4357/ad8636 |
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| author | Amr Hamada Kiran Jain Charles Lindsey Mitchell Creelman Niles Oien |
| author_facet | Amr Hamada Kiran Jain Charles Lindsey Mitchell Creelman Niles Oien |
| author_sort | Amr Hamada |
| collection | DOAJ |
| description | Active Regions (ARs) are regions of strong magnetic flux in the solar atmosphere. Understanding the global evolution of ARs is critical for solar magnetism as well as for accurate space-weather forecasting. We present the first far-side AR data set based on EUV observation and helioseismic measurements. For the EUV observations, we use synchronic maps at 304 Å comprised of observations from the Solar Dynamics Observatory/Atmospheric Imaging Assembly and the Solar TErrestrial RElations Observatory/Extreme UltraViolet Imager, in heliocentric orbit with direct vantages into the Sun’s far hemisphere. We used the brightening of the solar transition region in EUV/304 Å maps as a proxy for the magnetic regions. For the far-side helioseismic measurements, we used seismic phase-shift maps of the Sun’s far hemisphere, computed from helioseismic Dopplergrams observed by NSO/Global Oscillations Network Group (GONG). In this study, we present the first global EUV AR data set of the whole Sun, providing several basic parameters, such as location, area, tilt angle, EUV brightness, and latitudinal/longitudinal extents of the identified ARs. We also present a similar data set for the far-side GONG ARs where the helioseismic phase shift parameters are included. Helioseismic far-side GONG ARs are examined, and their success at predicting strong ARs is assessed. We discuss the temporal and spatial evolution for the EUV AR signatures and far-side GONG AR signatures during the ascending and maximum phases of Solar Cycle 24 (2010 May–2016 May). We examine the correlation between the helioseismic signatures and the respective EUV source distributions in the Sun’s far hemisphere. We present the first far-side AR butterfly diagram based on helioseismic measurements. |
| format | Article |
| id | doaj-art-b6c88c9844d24f6bb8196b7bee4bdc2a |
| institution | Kabale University |
| issn | 1538-4357 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IOP Publishing |
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| series | The Astrophysical Journal |
| spelling | doaj-art-b6c88c9844d24f6bb8196b7bee4bdc2a2024-12-04T05:59:11ZengIOP PublishingThe Astrophysical Journal1538-43572024-01-0197718510.3847/1538-4357/ad8636Far-side Active Regions Based on Helioseismic and EUV Measurements: A New Data Set for Heliospheric Machine Learning AdvancementsAmr Hamada0https://orcid.org/0000-0002-8900-8011Kiran Jain1https://orcid.org/0000-0002-1905-1639Charles Lindsey2https://orcid.org/0000-0002-5658-5541Mitchell Creelman3https://orcid.org/0009-0008-2557-3848Niles Oien4https://orcid.org/0009-0000-5113-2757National Solar Observatory , Boulder, CO 80303, USA ; ahamada@nso.eduNational Solar Observatory , Boulder, CO 80303, USA ; ahamada@nso.eduNorth West Research Associates , Boulder, CO 80301, USANational Solar Observatory , Boulder, CO 80303, USA ; ahamada@nso.eduNational Solar Observatory , Boulder, CO 80303, USA ; ahamada@nso.eduActive Regions (ARs) are regions of strong magnetic flux in the solar atmosphere. Understanding the global evolution of ARs is critical for solar magnetism as well as for accurate space-weather forecasting. We present the first far-side AR data set based on EUV observation and helioseismic measurements. For the EUV observations, we use synchronic maps at 304 Å comprised of observations from the Solar Dynamics Observatory/Atmospheric Imaging Assembly and the Solar TErrestrial RElations Observatory/Extreme UltraViolet Imager, in heliocentric orbit with direct vantages into the Sun’s far hemisphere. We used the brightening of the solar transition region in EUV/304 Å maps as a proxy for the magnetic regions. For the far-side helioseismic measurements, we used seismic phase-shift maps of the Sun’s far hemisphere, computed from helioseismic Dopplergrams observed by NSO/Global Oscillations Network Group (GONG). In this study, we present the first global EUV AR data set of the whole Sun, providing several basic parameters, such as location, area, tilt angle, EUV brightness, and latitudinal/longitudinal extents of the identified ARs. We also present a similar data set for the far-side GONG ARs where the helioseismic phase shift parameters are included. Helioseismic far-side GONG ARs are examined, and their success at predicting strong ARs is assessed. We discuss the temporal and spatial evolution for the EUV AR signatures and far-side GONG AR signatures during the ascending and maximum phases of Solar Cycle 24 (2010 May–2016 May). We examine the correlation between the helioseismic signatures and the respective EUV source distributions in the Sun’s far hemisphere. We present the first far-side AR butterfly diagram based on helioseismic measurements.https://doi.org/10.3847/1538-4357/ad8636Solar physicsSolar active regionsHelioseismologySolar extreme ultraviolet emissionSpace weatherSolar activity |
| spellingShingle | Amr Hamada Kiran Jain Charles Lindsey Mitchell Creelman Niles Oien Far-side Active Regions Based on Helioseismic and EUV Measurements: A New Data Set for Heliospheric Machine Learning Advancements The Astrophysical Journal Solar physics Solar active regions Helioseismology Solar extreme ultraviolet emission Space weather Solar activity |
| title | Far-side Active Regions Based on Helioseismic and EUV Measurements: A New Data Set for Heliospheric Machine Learning Advancements |
| title_full | Far-side Active Regions Based on Helioseismic and EUV Measurements: A New Data Set for Heliospheric Machine Learning Advancements |
| title_fullStr | Far-side Active Regions Based on Helioseismic and EUV Measurements: A New Data Set for Heliospheric Machine Learning Advancements |
| title_full_unstemmed | Far-side Active Regions Based on Helioseismic and EUV Measurements: A New Data Set for Heliospheric Machine Learning Advancements |
| title_short | Far-side Active Regions Based on Helioseismic and EUV Measurements: A New Data Set for Heliospheric Machine Learning Advancements |
| title_sort | far side active regions based on helioseismic and euv measurements a new data set for heliospheric machine learning advancements |
| topic | Solar physics Solar active regions Helioseismology Solar extreme ultraviolet emission Space weather Solar activity |
| url | https://doi.org/10.3847/1538-4357/ad8636 |
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